Error Research Articles

Hyperparameter Tuning of Load-Forecasting Models Using Metaheuristic Optimization Algorithms—A Systematic Review

Load forecasting is an integral part of the power industries. Load-forecasting techniques should minimize the percentage error while prediction future demand. This will inherently help utilities have an uninterrupted power supply. In addition to that, accurate load forecasting can result in saving large amounts of money. This article provides a systematic review based on the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) framework. This article presents a complete framework for short-term load forecasting using metaheuristic algorithms. This framework consists of three sub-layers: the data-decomposition layer, the forecasting layer, and the optimization layer. The data-decomposition layer decomposes the input data series to extract important features. The forecasting layer is used to predict the result, which involves different statistical and machine-learning models. The optimization layer optimizes the parameters of forecasting methods to improve the accuracy and stability of the forecasting model using different metaheuristic algorithms. Single models from the forecasting layer can predict the results. However, they come with their limitations, such as low accuracy, high computational burden, stuck to local minima, etc. To improve the prediction accuracy, the hyperparameters of these models need to be tuned properly. Metaheuristic algorithms cab be used to tune these hyperparameters considering their interdependencies. Hybrid models combining the three-layer methods can perform better by overcoming the issues of premature convergence and trapping into a local minimum solution. A quantitative analysis of different metaheuristic algorithms and deep-learning forecasting methods is presented. Some of the most common evaluation indices that are used to evaluate the performance of the forecasting models are discussed. Furthermore, a taxonomy of different state-of-the-art articles is provided, discussing their advantages, limitations, contributions, and evaluation indices. A future direction is provided for researchers to deal with hyperparameter tuning.

An Approach to Realize Generalized Optimal Motion Primitives Using Physics Informed Neural Networks

Abstract Autonomous manipulation is a challenging problem in field robotics due to uncertainty in object properties, constraints, and coupling phenomenon with robot control systems. Humans learn motion primitives over time to effectively interact with the environment. We postulate that autonomous manipulation can be enabled by basic sets of motion primitives as well, but do not necessitate mimicking human motion primitives. This work presents an approach to generalized optimal motion primitives using physics-informed neural networks. Our simulated and experimental results demonstrate that optimality is notionally maintained where the mean maximum observed final position percent error was 0.564% and the average mean error for all the trajectories was 1.53%. These results indicate that notional generalization is attained using a physics-informed neural network approach that enables near optimal real-time adaptation of primitive motion profiles.

High order recovery of geometric interfaces from cell-average data

We consider the problem of recovering multivariate characteristic functions u := χΩ from cell-average data on a coarse grid, motivated in particular by the accurate treatment of interfaces in finite volume schemes. While linear recovery methods are known to perform poorly, nonlinear strategies based on local reconstructions of the jump interface Γ := ∂Ω by geometrically simpler interfaces may offer significant improvements. We study two main families of local reconstruction schemes the first one based on nonlinear least-squares fitting, the second one based on the explicit computation of a polynomial-shaped curve fitting the data, which yields simpler numerical computations and high order geometric fitting. For each of them, we derive a general theoretical framework which allows us to control the recovery error by the error of best approximation up to a fixed multiplicative constant. Numerical tests in 2d illustrate the expected approximation order of these strategies. Several extensions are discussed, in particular the treatment of piecewise smooth interfaces with corners.

Evaluation of the psychometric properties of the Turkish version of the Skin-to-Skin Contact Scale for nurses.

Skin-to-skin contact is the practice with the highest level of evidence that increases the growth, development, and healing rate of the newborn. Neonatal nurses are also the best practitioners of skin-to-skin contact. This study examined the psychometric properties of the Turkish version of the Skin-to-Skin Contact Scale for nurses. This descriptive, correlational, and cross-sectional study was carried out with 226 neonatal and pediatric nurses between July 2022 and July 2023. The data were collected using an online questionnaire, including a descriptive information form and a skin-to-skin contact scale for nurses. Data were analyzed by explanatory and confirmatory factor analysis, Cronbach's alpha, and item-total score analysis. It was determined that the scale consisted of 20 items and four sub-dimensions and that those four sub-dimensions explained 53.01% of the total variance. All factor loads were higher than 0.30 in the explanatory and confirmatory factor analyses. All the fit indices were higher than 0.80, and the Root Mean Square Error of Approximation (RMSEA) was less than 0.080 in the confirmatory factor analysis. Cronbach's alpha was determined to be 0.89 for the total scale and greater than 0.70 for all sub-dimensions. The Skin-to-Skin Contact Scale for nurses was determined to be a valid and reliable measurement tool for Turkish nurses. It is recommended that the scale be used regularly in clinics to determine nurses' attitudes towards skin-to-skin contact.

Assessment of ADIS 16364 for the Examination of Ship Motions in the Free-Running Model

The ADIS 16364 instrument is frequently employed for direct measurement of ship motion on ships. However, the validation process for ADIS 16364, to assure its reliability in monitoring ship motion, has not yet been completed. The ship motion model test conducted at the hydrodynamics laboratory utilizes the free-running test technique in conjunction with the QUALISYS motion capture system and the ADIS 16364 device. The purpose of this assessment is to ascertain the instrument's appropriateness for performing ship motion testing. The ADIS device is composed of two components: an accelerometer and a gyroscope. These components are employed to quantify the acceleration of the ship's heave motion and the rotational velocity of its pitch and roll motions, respectively. Utilizing a motion capture system, the QUALISYS Motion Capture System records the motion of a ship model. The examination evaluates two discrete waves produced, comprising two cases of regular waves measuring 10 centimetres in height and 1.5 seconds in period and two cases of irregular waves measuring 16 centimetres in height and 1.75 seconds in period. The elevation motion data in the time domain is acquired from the measurements of the instrument via a wireless system. Following this, various numerical processing methods are implemented, including the moving average filter and cumulative trapezoidal numerical integration. As a result, the root mean square percentage error (RMSPE) discrepancies between the two measuring instruments for regular waves are restricted to a maximum of 5.7% for roll motion and fall below 4% for heave and pitch motions. In the results of the model test response, every movement in both the regular wave and irregular wave scenarios is the same because it does not have an RMSPE of more than 5%.

Ergonomic Improvement at a Distribution Center Using a Voice-Directed Feedback System to Manage Loading Trucks

This field study reports on a wireless, wearable, automated voice-directed system where truck loaders at a distribution center wear a headset to listen to instructions and speak into a microphone to load pallets of product into delivery trucks accurately. The system was designed to provide immediate and corrective feedback to load pallets in reverse-stop sequence for all multi-stop routes. The voice-directed system intervention was instrumental in reducing the number of pallets loaded out of sequence to 0.015%, based on approximately 175 weekly routes, amounting to a decrease of an out-of-sequence percentage error by 99%.

Understanding the effect of occupational stress on sleep quality in firefighters: the modulating role of depression and burnout.

Sleep quality of firefighters can be negatively affected by occupational stressors. A cross-sectional investigation was conducted to understand how work-related stress, post-traumatic stress, burnout and depression collectively contribute to sleep quality. Professional firefighters in Northern Iran completed a survey comprised of demographic information, the Pittsburgh Sleep Quality Index, HSE's Stress Indicator Tool, the Posttraumatic Stress Disorder Checklist, Maslach's Burnout Inventory, and the Beck Depression Inventory during a work rest break. Data were analysed using structural equation modelling. Mean age of the 2339 firefighters who completed the survey was 32.30 (5.74) years. Most experienced poor sleep quality, scoring above the established cut-off of 5. Levels of work-related stress, post-traumatic stress, burnout and depression were high. Fit indices of the final theoretical model were all adequate: the obtained and adjusted goodness-of-fit indices were 0.925 and 0.917 respectively. Comparative, and incremental fit indices were 0.946 and 0.948 respectively. Root mean squared error of approximation was 0.061. Post-traumatic stress was directly and indirectly related to sleep quality through eight paths, modulated by burnout variables and depression. Work-related stress was negatively related to sleep quality through four paths modulated, by burnout variables and depression. The findings illustrate the complex relationships of work-related stress and post-traumatic stress and sleep quality. High levels of poor sleep quality in this occupation emphasise the need to develop targeted and sustainable interventions to manage occupational stressors, burnout and depression to improve sleep quality in firefighters.

A Boolean sum interpolation for multivariate functions of bounded variation

This paper deals with the approximation error of trigonometric interpolation for multivariate functions of bounded variation in the sense of Hardy-Krause. We propose interpolation operators related to both the tensor product and sparse grids on the multivariate torus. For these interpolation processes, we investigate the corresponding error estimates in the Lp norm for the class of functions under consideration. In addition, we compare the accuracy with the cardinality of these grids in both approaches.

Discrete‐Time Optimal Control of State‐Constrained Nonlinear Systems Using Approximate Dynamic Programming

ABSTRACTThis article investigates the optimal control problem (OCP) for a class of discrete‐time nonlinear systems with state constraints. First, to overcome the challenge caused by the constraints, the original constrained OCP is transformed into an unconstrained OCP by utilizing the system transformation technique. Second, a new cost function is designed to alleviate the effect of system transformation on the optimality of the original system. Further, a novel off‐policy deterministic approximate dynamic programming (ADP) scheme is developed to obtain a near‐optimal solution for the transformed OCP. Compared to existing off‐policy deterministic ADP schemes, the developed scheme relaxes the requirement on the learning data and saves computing resources from the perspective of training neural networks. Third, considering approximation errors, we analyze the convergence and stability of the developed ADP scheme. Finally, the developed ADP with the designed cost function is tested in two numerical cases, and simulation results confirm its effectiveness.

How Sharp Are Error Bounds? –Lower Bounds on Quadrature Worst-Case Errors for Analytic Functions–

How Sharp Are Error Bounds? –Lower Bounds on Quadrature Worst-Case Errors for Analytic Functions–

Automatic differential kinematics of serial manipulator robots through dual numbers

Dual Numbers are an extension of real numbers known for its capability of performing exact automatic differentiation of one-valued functions theoretically without error approximation. Also, Differential Kinematics of robots involves the computation of the Jacobian, which is a matrix of partial derivatives of the Forward Kinematic equations with respect to the robot’s joints. Thus, to perform the automatic calculation of the Jacobian matrix, this paper presents an extension of dual numbers composed of a scalar real part and a vector dual part, where the real part represents the angular value of the robot joint, and the dual part represents the direction of the corresponding partial derivative for each joint. The presented method was implemented in Matlab through Object Orientes Programming (OOP), and the results for calculating the Jacobian of the KUKA KR 500 robot model for 1000 random postures were subsequently compared in terms of execution time and Mean Squared Error (MSE) with other conventional methods: the geometric method, the symbolic method, and the finite difference method. The results showed a significant improvement in the computing time for calculating the Jacobian of the robotic model compared to the other methods, as well as a minimum MSE having as reference the numerical value of the symbolic calculations.

Comparative thermal model analysis and experimental validation for predicting performance of a pyramidal solar still with integrated pulsating heat pipe

Developing nations face a dire situation as water scarcity and pollution significantly impact various aspects of life. It's crucial to take action now to address these pressing issues and ensure a sustainable future for all. Solar desalination processes emerge as a promising solution to these pressing problems in water purification technologies.This paper reports the thermal modeling and experimental results of two solar still designs, namely (i) Pyramidal solar still with pulsating heat pipe (PHP), Modified pyramidal solar still (MPSS), and (ii) conventional pyramidal solar still (CPSS). This study uses energy balance equations to focus on MPSS and CPSS thermal modeling. In the MPSS, a PHP, in conjunction with a solar collector, provides external heat to basin water. Several models, including Dunkel, Kumar and Tiwari, Chen, and Zheng Hongfei, are utilized to estimate the performance of both MPSS and CPSS. Extensive experiments have been conducted for validation purposes. Key parameters considered for prediction and comparison include evaporative heat transfer coefficient, convective heat transfer coefficient, total heat transfer coefficient, and hourly yield. It is noted that the Kumar and Tiwari model demonstrates a superior ability to predict cumulative yield, with a percentage error of 5.81 % and 5.9 % for MPSS and CPSS, respectively, compared to the experimental cumulative yield. The theoretical average basin water temperature observed in MPSS is 64.56 °C, and CPSS is 58.8 °C. The enhancement in temperature is attributed to the supplementary heat provided by the PHP.

Role of Meaningful Social Participation and Technology Use in Mitigating Loneliness and Cognitive Decline Among Older Adults.

Community social participation aids dementia prevention and alleviates loneliness among older adults. Incorporating occupational therapy using information and communications technology (ICT) could potentially delay dementia onset and reduce loneliness. To quantify how meaningful social participation, participation frequency, ICT use, and expanded social networks influence cognitive function and loneliness among socially active older Japanese adults. Cross-sectional exploratory study using structural equation modeling. Meetings organized by older adults at seven community gathering places in Osaka Prefecture, Japan. One hundred thirteen healthy older adult cohort members. Cognitive function assessed via Mini-Cog; loneliness assessed via the condensed UCLA Loneliness Scale. The final model demonstrated excellent fit, χ2(23) = 28.291, p = .205 (root mean square error of approximation = .045, 90% confidence interval [.000, .094]; confirmatory factor index = .995; Tucker-Lewis Index = .993). ICT use directly affected social networks (β = 0.472), which directly influenced participation frequency (β = 0.324) and meaningful social participation (β = 0.381). The indirect effect of meaningful participation significantly improved cognitive function (β = 0.237). The only indirect effect of meaningful interpersonal participation was a reduction in loneliness (β = -0.235). ICT use contributes to the expansion of social networks among elderly people. Furthermore, the frequency of social participation and the meaningfulness of such participation are related to reduction in loneliness and maintenance of cognitive function. Although the frequency of social participation was not directly related to these outcomes, the results suggest that meaningful social participation may play an important role in reducing loneliness and maintaining cognitive function. Plain-Language Summary: The promotion of social participation among older people is a global phenomenon, driven by the recognition of its positive relationship with cognitive function and the alleviation of loneliness. Nevertheless, older people's social participation is constrained by a combination of physical and social factors. To address this issue, there has been a push to promote social participation based on information and communications technology (ICT). However, no specific study has been conducted on occupational therapists' perspective in capturing social participation and the use of ICT. The findings of this study show that using ICT has the potential to enhance opportunities for social interaction for older adults, thereby improving the quality and quantity of social participation. The quality of social participation was identified as the sole factor that had a positive impact on cognitive function and loneliness. This study suggests the need for occupational therapists to consider means of facilitating the use of ICTs among older adults as well as interventions that use occupational therapy theory to enhance the meaningfulness of existing social participation opportunities.

Hybrid modality dual-energy imaging aggregating complementary advantages of kV-CT and MV-CBCT: concept proposal and clinical validation

Megavoltage cone-beam CT (MV-CBCT) is advantageous in metal artifact reduction during Image-Guided Radiotherapy (IGRT), although it is limited by poor soft tissue contrast. This study proposed and evaluated a novel hybrid modality dual-energy (DE) imaging method combining the complementary advantages of kV-CT and MV-CBCT.
Approach: The kV-CT and MV-CBCT images were acquired on a planning CT scanner and a Halcyon linear accelerator respectively. After rigid registration, images of basis materials were generated using the iterative decomposition method in the volumetric images. The decomposition accuracy was quantitatively evaluated on a Gammex 1472 phantom. The performance of contrast enhancement and metal artifact reduction in virtual monochromatic images were evaluated on both phantom and patient studies.
Main results: Using the proposed method, the mean percentage errors for RED and SPR were 0.90% and 0.81%, outperforming the clinical single-energy mapping method with mean errors of 1.28% and 1.07%, respectively. The contrasts of soft-tissue insets were enhanced by a factor of 2~3 at 40 keV compared to kV-CT. The standard deviation in the metal artifact area was reduced by ~67%, from 42 HU (kV-CT) to 14 HU (150 keV monochromatic). The head and neck patient test showed that the percent error of soft-tissue RED in the metal artifact area was reduced from 18.1% (HU-RED conversion) to less than 1.0% (the proposed method), which was equivalent to the maximum dosimetric difference of 28.7% based on the patient-specific plan.
Significance: Without hardware modification or extra imaging dose, the proposed hybrid modality method enabled kV-MV DE imaging, providing improved accuracy of quantitative analysis, soft-tissue contrast and metal artifact suppression for more accurate IGRT.&#xD.

MRI Super-Resolution with Partial Diffusion Models.

Diffusion models have achieved impressive performance on various image generation tasks, including image super-resolution. Despite their impressive performance, diffusion models suffer from high computational costs due to the large number of denoising steps. In this paper, we proposed a novel accelerated diffusion model, termed Partial Diffusion Models (PDMs), for magnetic resonance imaging (MRI) super-resolution. We observed that the latents of diffusing a pair of low- and high-resolution images gradually converge and become indistinguishable after a certain noise level. This inspires us to use certain low-resolution latent to approximate corresponding high-resolution latent. With the approximation, we can skip part of the diffusion and denoising steps, reducing the computation in training and inference. To mitigate the approximation error, we further introduced 'latent alignment' that gradually interpolates and approaches the high-resolution latents from the low-resolution latents. Partial diffusion models, in conjunction with latent alignment, essentially establish a new trajectory where the latents, unlike those in original diffusion models, gradually transition from low-resolution to high-resolution images. Experiments on three MRI datasets demonstrate that partial diffusion models achieve competetive super-resolution quality with significantly fewer denoising steps than original diffusion models. In addition, they can be incorporated with recent accelerated diffusion models to further enhance the efficiency.

Fundamental tests of P and CP symmetries using octet baryons at the J/ψ threshold

We systematically investigate tests of the parity P and the combined parity and charge-conjugate CP symmetries from differential angular distributions of J/ψ decaying into the lowest-lying baryon pairs at BESIII and the next-generation super tau-charm facilities (STCFs). Large corrections from Z and W exchange induced parity-violating effects are found for J/ψ decays with large logarithms resummed up to O(αs). The parity-violating asymmetries on the production and the decay sides of J/ψ are both estimated to be of O(10−4), thus barely observable with the 10 billion J/ψ events currently collected at BESIII. Nevertheless, these asymmetries utilizing the current BESIII data already permit a measurement of the weak mixing angle with an absolute uncertainty δsw2≈0.09, corresponding to the first determination of sw2 at the J/ψ threshold. In the future, STCFs are estimated to improve this bound by a factor of ∼20 to δsw2≈0.005 within one year based on luminosity rescaling. We also obtain the 95% confidence level upper bounds on the electric dipole moments of the octet baryons, which are of O(10−18) e cm for BESIII and O(10−19) e cm for STCFs. These bounds are improved by 2 to 3 orders of magnitude in comparison with the only existing one on Λ from Fermilab. The method discussed in this work also paves a way for a first and direct measurement of the Ξ and Σ electric dipole moments. Published by the American Physical Society 2024

A plastic correction algorithm for full-field elasto-plastic finite element simulations: critical assessment of predictive capabilities and improvement by machine learning

AbstractThis paper introduces a new local plastic correction algorithm that is aimed at accelerating elasto-plastic finite element (FE) simulations for structural problems exhibiting localised plasticity (around e.g. notches, geometrical defects). The proposed method belongs to the category of generalised multi-axial Neuber-type methods, which process the results of an elastic prediction point-wise in order to calculate an approximation of the full elasto-plastic solution. The proposed algorithm relies on a rule of local proportionality, which, in the context of J2 plasticity, allows us to express the plastic correction problem in terms of the amplitude of the full mechanical tensors only. This lightweight correction problem can be solved for numerically using a fully implicit time integrator that shares similarities with the radial return algorithm. The numerical capabilities of the proposed algorithm are demonstrated for a notched structure and a specimen containing a distribution of spherical pores, subjected to monotonic and cyclic loading. As a second point of innovation, we show that the proposed local plastic correction algorithm can be further accelerated by employing a simple meta-modelling strategy, with virtually no added errors. At last, we develop and investigate the merits of a deep-learning-based corrective layer designed to reduce the approximation error of the plastic corrector. A convolutional architecture is used to analyse the neighbourhoods of material points and outputs a scalar correction to the point-wise Neuber-type predictions. This optional brick of the proposed plastic correction methodology relies on the availability of a set of full elasto-plastic finite element solutions to be used as a training data-set.

Development and validation of Parents’ Health Literacy Scale on Preventing Road Traffic Injuries for children aged 0–6 years in China

BackgroundRoad traffic injuries are the leading cause of death in children. Parents’ health literacy (HL) is closely related to child safety, especially for the young children. This study aimed to...

A comparative study of crop evapotranspiration estimation in maize using empirical methods, pan evaporation and satellite-based remote sensing technique

A research study was conducted at the Agricultural College and Research Institute, Coimbatore to estimate the evapotranspiration (ET) of maize crop (Zea mays) over 2 consecutive seasons in 2022-2023. Among the different methods used to estimate crop evapotranspiration, the Food and Agricultural Organization Penman-Monteith model (FAO P-M) is widely recognized as the standard approach for ET estimation. This study aimed to compare the effectiveness of three alternative methods - Thornthwaite (TW), NDVI-based and pan methods against the FAO Penman-Monteith (P-M) model in estimating maize evapotranspiration. Meteorological data were collected from the TNAU weather station spanning the period from 2022 to 2023.The performance of the estimation methods was assessed using statistical metrics such as coefficient of determination (R2), root mean squared error (RMSE), percentage error and mean bias error. The findings revealed that the NDVI-based method, relying on satellite data, provided higher accuracy in estimating maize evapotranspiration compared to the FAO PM method. Specifically, the NDVI-based method achieved the highest coefficient of determination (R2) of 0.87 and 0.89, the lowest RMSE of 12.44 mm/month and 15.5 mm/month, the lowest percentage error of 4.8 % and 9.00 % and the lowest mean bias error of 5.5 and 7.85 for the first and second seasons respectively. This study highlights the effectiveness of the NDVI-based ET estimation method for accurately assessing maize evapotranspiration. While the FAO-56 Penman-Monteith method is highly regarded for its accuracy in both theoretical and practical contexts, the comparative evaluation presented in this paper offers valuable insights for selecting alternative methods that require less data, particularly in regions with limited data availability.

Psychometric Properties of the Persian Version of the Satisfaction With Life Scale (SWLS) in Iranian Older Adults

Objectives: To investigate the psychometric properties of the persian version of the Satisfaction With Life Scale (SWLS-P) among older adults in Tabriz. Design: A cross-sectional study. Setting(s): Tabriz, the capital of East Azerbaijan province, Iran. Participants: A representative sample of 1362 (768 females and 594 males) community-dwelling people aged≥60 participated in the current study. Outcome measures: The psychometric properties of the SWLS-P were evaluated. The standard translate/back-translate procedure was applied. Then, using an expert panel, the face and content validities were assessed. Exploratory and confirmatory factor analysis (EFA and CFA) and structural equation modeling (SEM) were used to investigate the factorial structure, and data were analyzed using SPSS software version 23 and AMOS version 18. Results: Cronbach’s alpha calculated for the SWLS-P was 0.883, showing desirable internal consistency and reliability for the SWLS. Furthermore, CFA confirmed the single-factor structure of the Persian version of the scale and indicated an appropriate fit, with a root mean square error of approximation (RMSEA) of 0.049, a comparative fit index (CFI) of 0.997, a Tucker-Lewis Index (TLI) of 0.991, and a Chi-square to degrees of freedom (DF) ratio of 4.289. Conclusions: The results supported the validity and reliability of the SWLS-P for use with Iranian older adults.